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Installation

PDAL Python provides Python bindings for the PDAL library. You’ll need both the PDAL base library and the Python package installed to get started.

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Prerequisites

Before installing PDAL Python, ensure you have:
  • PDAL base library 2.7 or higher: The core PDAL library must be installed on your system
  • Python 3.9 or higher: PDAL Python supports Python 3.9, 3.10, 3.11, and 3.12
  • NumPy 1.22 or higher: Required for array operations
The PDAL Python bindings require the PDAL base library to be installed separately. Source code and installation instructions for PDAL can be found at pdal.io and GitHub.

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Install from PyPI

The simplest way to install PDAL Python is using pip:
1

Install PDAL Python

Run the following command to install PDAL Python and its dependencies:
pip install PDAL
This will automatically install NumPy if it’s not already present.
2

Verify installation

Verify that PDAL Python is installed correctly:
import pdal
print(pdal.__version__)
print(pdal.info)
This should display the version number and PDAL configuration information.

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Developer installation

If you’re developing PDAL Python or need a custom build, you can install from source with full control over the build configuration.
1

Install build dependencies

Install the required build tools:
pip install pybind11[global]
pip install numpy
pip install scikit-build-core
2

Clone the repository

Clone the PDAL Python repository:
git clone https://github.com/PDAL/python
cd python
3

Build and install

Install in editable mode with custom build settings using scikit-build-core:
python -m pip install \
    -Cbuild-dir=build \
    -e \
    . \
    --config-settings=cmake.build-type="Debug" \
    -vv \
    --no-deps \
    --no-build-isolation
This command:
  • Sets the build directory to build
  • Installs in editable mode (-e)
  • Configures a Debug build (change to “Release” for production)
  • Enables verbose output (-vv)
  • Skips dependency resolution and build isolation for development
Developers can control many build settings including debug builds and library installation paths using scikit-build-core configuration settings.

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Optional dependencies

PDAL Python integrates with additional libraries for extended functionality:

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Mesh support

For mesh creation and export capabilities: 
pip install meshio
This enables the Pipeline.get_meshio() method for working with triangulated meshes.

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DataFrame support

For pandas and GeoPandas integration: 
pip install pandas
pip install geopandas
This enables Pipeline.get_dataframe() and Pipeline.get_geodataframe() methods.

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Platform-specific notes

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Installing PDAL base library

The installation method for the PDAL base library varies by platform: Ubuntu/Debian: 
sudo apt-get install libpdal-dev pdal
macOS (Homebrew): 
brew install pdal
Windows: Use the OSGeo4W installer or Conda: 
conda install -c conda-forge pdal python-pdal
From source: See the PDAL documentation for detailed build instructions.

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Next steps

Quick start

Create your first PDAL pipeline and start processing point cloud data

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